Optimal Biased Association Scheme with Heterogeneous User Distribution in HetNets

Kong, Fancheng; Sun, Xinghua; Zhu, Hongbo

doi:10.1007/s11277-015-3102-y

Cited by 5 publications

(10 citation statements)

References 19 publications

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“…A significant increase in system throughput and capacity is noted; however biased Micro BSs performance was degraded by strong interference from the Macro BS. Some research efforts [183][184][185][186] focused on optimizing the value of the bias to maximize network utility, throughput, and reduce outage probability. Also, [187] introduced the rate-biased user association algorithm as another solution to overcome the drawbacks of max-SINR user association.…”

Section: Related Workmentioning

confidence: 99%

Optimizing Macro and Micro Base Stations Locations and User Associations in Heterogeneous Wireless Networks

Hassan¹

2021

Preprint

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Heterogeneous Networks (HetNets) have gained the attraction of the communication industry recently, due to their promising ability to enhance the performance of future broadband Fifth Generation (5G) networks and are integral parts of 5G systems. They can be viewed in multi-dimensional space where, each slice represents a unique tier that has its own Base Station (BS)s and User Equipment (UE)s. Different tiers cooperate with each other for their mutual benefit. Data can be interactively exchanged among the tiers, and UEs have the flexibility to switch between the tiers. The cells in such a heterogeneous cellular networks have variable sizes, shapes, and coverage regions. However, in HetNets with ultra dense BSs, the distance between them gets very small and, they suffer from very high levels of mutual interference. To improve the performance of HetNets, we have done multiple contributions in this dissertation. First, we have developed analytical derivations for optimizing pilot sequence length which is a very crucial factor in acquiring the Channel State Information (CSI) and the channel estimation process in general. Poisson Point Process (PPP) has been widely used to allocate BSs among various tiers so far. However, BS locations obtained using PPP approach may not be optimum to reduce interference. Therefore, in this dissertation, BSs locations are optimized to reduce the interference and improve the coverage and received signal power. Also, we have derived expressions for static UEs coverage probability and network energy efficiency in HetNets. A proper UE association algorithm for HetNets is a great challenge. The classic max-Signal to Interference and Noise Ratio (SINR) or max-received signal strength (RSS) user association algorithms are inappropriate solutions for HetNets as UEs in this context will tend to connect to the Macro BS, which is the one with the highest signal power. A severe load imbalance and significant inefficiency arises and impacts the performance. The aforementioned algorithms tend to associate UEs to BSs with the best received signal power or signal quality. In HetNets, usually Macro BSs are the ones transmitting the strongest signals; hence most UEs tend to associate with the Macro BS leaving Micro BSs with less load. Also, the conventional max-SINR and max-RSS algorithms do not provide adequate results in multi-tier systems. We suggest two centralized algorithms, LSTD and RTLB, for an even UE association to provide fair load distribution. However RTLB outperforms LSTD in real time scenarios as it easily and quickly adapts to rapid network changes. Furthermore, we consider the mobility of nodes. We derive coverage probability for moving UEs considering both handover and no handover scenarios. Proposed algorithms are fast enough to associate the moving users to different Micro and Macro BSs appropriately in real time. Our algorithms are proved to be feasible and provide a path towards attainable future communication systems.

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Section: Related Workmentioning

confidence: 99%

Optimizing Macro and Micro Base Stations Locations and User Associations in Heterogeneous Wireless Networks

Hassan¹

2021

Preprint

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“…A number of further research efforts [7][8][9][10] focused on optimizing the value of the bias under various constraints. Namely:…”

Section: Bias Based User Associationmentioning

confidence: 99%

“…The authors of [24] proposed a load-balancing scheme for an operator-deployed cellular-WLAN HetNet to optimize system throughput. The authors in [8] proposed a distributed belief propagation (BP) algorithm to optimize the weighted proportional fairness with various UE priorities. Also, the authors in [34] designed two offloading algorithms to maximize the weighted sum of long-term rates.…”

Section: Other User Association Algorithmsmentioning

confidence: 99%

An Optimum User Association Algorithm in Heterogeneous 5G Networks Using Standard Deviation of the Load

Hassan

Fernando

2020

Electronics

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Fifth-generation (5G) wireless networks and beyond will be heterogeneous in nature, with a mixture of macro and micro radio cells. In this scenario where high power macro base stations (MBS) coexist with low power micro base stations (mBS), it is challenging to ensure optimal usage of radio resources to serve users with a multitude of quality of service (QoS) requirements. Typical signal to interference and noise ratio (SINR)-based user allocation protocols unfairly assign more users to the high power MBS, starving mBS. There have been many attempts in the literature to forcefully assign users to mBS with limited success. In this paper, we take a different approach using second order statistics of user data, which is a better indicator of traffic fluctuations. We propose a new algorithm for user association to the appropriate base station (BS) by utilizing the standard deviation of the overall network load. This is done through an exhaustive search of the best user equipment (UE)–BS combinations that provide a global minimum to the standard deviation. This would correspond to the optimum number of UEs assigned to every BS, either macro or micro. We have also derived new expressions for coverage probability and network energy efficiency for analytical performance evaluation. Simulation results prove the validity of our proposed methods to balance the network load, improve data rate, average energy efficiency, and coverage probability with superior performance compared with other algorithms.

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“…The optimal biasing factor for BSs of each tier was obtained therein to maximize the rate coverage. With a similar PPP model, the biasing factor was optimized in [9], [10] by maximizing the logarithm of the mean user rate.…”

Section: Introductionmentioning

confidence: 99%

“…With fixed locations of BSs and users, no tractable expression of a performance metric such as the signal-to-interference-plus-noise ratio (SINR) or rate coverage can be derived, and the optimal biasing factor could only be found empirically. Stochastic geometry was then adopted in [5]- [10] to characterize the spatial distributions of BSs and users, and to quantify the average performance metric of the network. For example, a Poisson point process (PPP) was adopted in [7], [8] to represent the irregular deployment of the BSs.…”

Section: Introductionmentioning

confidence: 99%

Delay-Optimal Biased User Association in Heterogeneous Networks

Kong

Sun

Leung

et al. 2017

IEEE Trans. Veh. Technol.

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In heterogeneous networks (HetNets), load balancing among different tiers can be effectively achieved by a biased user association scheme with which each user chooses to associate with one base station (BS) based on the biased received power. In contrast to previous studies where a BS always has packets to transmit, we assume in this paper that incoming packets intended for all the associated users form a queue in the BS. In order to find the delay limit of the network to support realtime service, we focus on the delay optimization problem by properly tuning the biasing factor of each tier. By adopting a thinned Poisson point process (PPP) model to characterize the locations of BSs in the busy state, an explicit expression of the average traffic intensity of each tier is obtained. On that basis, an optimization problem is formulated to minimize a lower bound of the network mean queuing delay. By showing that the optimization problem is convex, the optimal biasing factor of each tier can be obtained numerically. When the mean packet arrival rate of each user is small, a closed-form solution is derived. The simulation results demonstrate that the network queuing performance can be significantly improved by properly tuning the biasing factor. It is further shown that the network mean queuing delay might be improved at the cost of a deterioration of the network signal-to-interference ratio (SIR) coverage, which indicates a performance tradeoff between real-time and non-realtime traffic in HetNets.Index Terms-heterogeneous network, biasing factor, average traffic intensity, network mean queuing delay

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Optimal Biased Association Scheme with Heterogeneous User Distribution in HetNets

Cited by 5 publications

References 19 publications

Optimizing Macro and Micro Base Stations Locations and User Associations in Heterogeneous Wireless Networks

Optimizing Macro and Micro Base Stations Locations and User Associations in Heterogeneous Wireless Networks

An Optimum User Association Algorithm in Heterogeneous 5G Networks Using Standard Deviation of the Load

Delay-Optimal Biased User Association in Heterogeneous Networks

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